Abstract
Abstract
This paper mainly studies the application of artificial intelligence and machine learning in the field of stock investment. The principles and characteristics of KNN, k-Means, bisecting k-Means, and ANN algorithms are studied to compare the effects, similarities and differences of different algorithms. The algorithms are implemented through Python programs for stock analysis. According to the P/E ratio, dividend rate, fixed asset turnover rate, gross profit margin and other indicators of each stock, the stocks are classified and clustered to predict the stock development prospects and provide reference for selecting appropriate investment strategies.
Subject
General Physics and Astronomy
Reference10 articles.
1. Stock market index prediction using artificial neural network;Moghaddam;Journal of Economics Finance & Administrative Science,2016
2. Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques;Patel;Expert Systems with Applications,2015
3. A review of the application of machine learning in stock investment;Sun,2019
4. Nonlinear index prediction;Zemke;Physica A,1999
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